Abstract

Real-time visualization of volumetric data is increasingly used by physicians and scientists. Enhanced depth perception in Direct Volume Rendering (DVR) plays a crucial role in applications such as clinical decision making. Our goal is to devise a flexible blurring method in DVR and ultimately improve depth perception in real-time DVR using synthetic depth of field (DoF) effect. We devised a permutation-based stochastic sampling method for ray casting to render images with DoF effect. Our method uses 2D blurring kernels in 3D space for each sample on a ray. Furthermore, we reduce the number of required samples for each kernel of size n2 from n2 to only 2 samples. This method is flexible and can be used for DoF, focus-context blurring, selective blurring, and potentially for other photographic effects such as the tilt effect.